This invention addresses development and demonstration of a small unmanned aerial system (sUAS) detection system that operates by using machine vision and deep learning to address classification of a sUAS as friendly or foe. A wide angle video camera, an array of directional microphones, and an optional mmWave radar stream the raw information to a processor such as a graphics processing unit (GPU).
Existing systems solely based on radar are inefficient in identifying a friendly or foe sUAS and can easily get confused with the approaching birds. They are also not capable to jam advanced guidance system of some sUASs. Moreover, the mechanical rotating scanner of conventional radars can be readily detected by a sUAS. The system disclosed herein solves problems and enables ready detection of drones, foe or friendly. Upon detection of the adversary sUAS, capturing nets that are commercially available can be used to neutralize the approaching sUAS by a soft landing.
Accordingly, there is a need in the art for improved drone detection.